Statistical Methods for the Analysis of Spatial and Temporal Patterns in Cancer Data-The Surveillance Research Program (SRP) has developed a series of statistical methods for the analysis of spatial patterns in cancer data. These include a spatial scan statistic (SaTScan), a spatial outlier detection tool (MGPS), a median-based spatial smoother (Headbang), and a spatial-temporal model of cancer incidence. SRP has also developed a number of statistical methods to detect non-spatial patterns in cancer surveillance data like Joinpoint, a linear spline tool to detect changes in temporal trends. SRP currently uses these tools in many ways for cancer surveillance and reporting activities. There is also interest in applying data visualization and experimental design techniques to quality control reliability studies.